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Composite sampling: A novel method to accomplish observational economy in environmental studies: A monograph introduction

机译:复合采样:在环境研究中实现观测经济的新方法:专着介绍

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This monograph on composite sampling, co-authored by Patil, Gore, and Taillie provides, for the first time, a most comprehensive statistical account of composite sampling as an ingenious environmental sampling method to help accomplish observational economy in a variety of environmental and ecological studies. Sampling consists of selection, acquisition, and quantification of a part of the population. But often what is desirable is not affordable, and what is affordable is not adequate. How do we deal with this dilemma? Operationally, composite sampling recognizes the distinction between selection, acquisition, and quantification. In certain applications, it is a common experience that the costs of selection and acquisition are not very high, but the cost of quantification, or measurement, is substantially high. In such situations, one may select a sample sufficiently large to satisfy the requirement of representativeness and precision and then, by combining several sampling units into composites, reduce the cost of measurement to an affordable level. Thus composite sampling offers an approach to deal with the classical dilemma of desirable versus affordable sample sizes, when conventional statistical methods fail to resolve the problem. Composite sampling, at least under idealized conditions, incurs no loss of information for estimating the population means. But an important limitation to the method has been the loss of information on individual sample values, such as the extremely large value. In many of the situations where individual sample values are of interest or concern, composite sampling methods can be suitably modified to retrieve the information on individual sample values that may be lost due to compositing. In this monograph, we present statistical solutions to these and other issues that arise in the context of applications of composite sampling. The monograph is published in the Monograph Series: Environmental and Ecological Statistics
机译:这本由Patil,Gore和Taillie合着的有关复合采样的专着首次提供了最全面的复合采样统计信息,将其作为一种巧妙的环境采样方法来帮助完成各种环境和生态研究中的观测经济。抽样包括部分人口的选择,获取和量化。但是通常,人们所期望的是负担不起的,而人们负担得起的则是不够的。我们如何应对这种困境?在操作上,复合采样识别选择,采集和定量之间的区别。在某些应用中,通常的经验是选择和获取的成本不是很高,但是量化或测量的成本却很高。在这种情况下,可以选择足够大的样本以满足代表性和精确度的要求,然后通过将多个采样单元组合为复合材料,将测量成本降低到可承受的水平。因此,当传统的统计方法无法解决问题时,复合采样提供了一种方法来处理理想样本量与可负担样本量之间的经典难题。至少在理想条件下,复合抽样不会导致估计总体均值的信息丢失。但是该方法的一个重要局限性是单个样本值(例如极大值)的信息丢失。在关注或关注单个样本值的许多情况下,可以对复合采样方法进行适当修改,以检索有关可能由于合成而丢失的单个样本值的信息。在本专着中,我们提出了针对在复合采样应用中出现的这些问题和其他问题的统计解决方案。该专着发表在《专着系列:环境与生态统计》上

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